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Summary: Atlas to Image-with-Tumor Registration based
on Demons and Deformation Inpainting
Hans Lamecker1,2
, Xavier Pennec2
1
Zuse Institute Berlin (ZIB), Germany,
2
Asclepios Research Project, INRIA, France
Abstract. This paper presents a method for nonlinear registration of
images, where there exists no one-to-one correspondence in parts of the
image. Such a situation occurs for instance in the case where an atlas of
normal anatomy shall be matched to pathological data, such as tumors,
resections or lesions. Our idea is to use local confidence weights and
to model pathological regions with zero confidence. We integrate this
concept into the efficient and publicly available diffeomorphic demons
registration framework. Finally, we show that this process better captures
deformations in high-confidence regions than without using the proposed
modification. Furthermore, it is easy to implement and runs faster than
previous approaches.
1 Introduction
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